As the mechanisms by which cells control the expression of their genetic code become better understood, concepts developed to aid the engineering of control systems in the mechanical and electrical arts are becoming increasingly applicable to the non-deterministic (“stochastic”) systems that control the biochemical activities of living cells.
Control systems engineering relies heavily on permitting or preventing the passage of a signal by means of a switch. The modern computer is an elaborate system of binary (“on/off”) switches (embodied in, e.g., signal diodes or their equivalent). The engineer arranges sets of switches to form logic gates (or “logic circuits”) according to principles of formal logic such that one or more signals entering the gate (“inputs”) contributes something (including nothing at all) to the gate's output. A gate determines its output by “evaluating” its inputs. The evaluation depends on how the gate's switches are arranged. One of the simplest gates (two switches) is an elementary “AND” gate. It requires two distinct inputs to open. If one or both inputs are absent (i.e., at least one switch is “off”), the gate remains closed. There is no output from it. A control system typically comprises a plurality of gates, variously interconnected to form a so-called logic evaluator. Control systems are typically coupled to a “controlled” system, and at least some of the inputs to the control system arise from the controlled system. Thus, one of the uses of the output of the control system is to feed back to the controlled system information about the state of the controlled system.
In the case of biomolecular control systems, the “switch,” is a molecule whose chemical activity (1) exerts an influence on a (bio)chemical process, and (2) is itself affected by a (bio)chemical process. Since virtually all chemically active biomolecules in living systems mediate at least one process within a network of interacting processes, these molecular “switches” participate in an enormously complicated set of logic gates that work together to control a living system such as a cell.
Despite the complexity one confronts when viewing homeostasis in a living system as an engineered control system, elements of living systems have been isolated and used to engineer control systems. For example, Schneider et al., in “Molecular Computing Elements, Gates and Flip-Flops” U.S. Pat. No. 6,774,222, described a molecular gate based on a nucleic acid, preferably double-stranded DNA. The nucleic acid has the properties of a switch because it has more than one binding site, each specific for its own ligand. A plurality of such switches may be arranged in various configurations, enabling the construction of logic gates variously activable by one or more binding ligands.
Benenson et al., in “An Autonomous Molecular Computer for Logical Control of Gene Expression” Nature 429:423-429 (2004), described a “molecular computer” that searches for a particular set of four indicators which, when the “computer” finds them all present, a gate opens and releases a drug or a suppressor (viz., antisense ssDNA). The paper demonstrates that “stochastic computing” (wherein purely binary data, i.e., “1” or “0,” are replaced by “probably 1” and “probably 0” data) can provide reliable results if the number of parallel “computations” (in this case, individual contacts between molecules) is very large. The paper demonstrates, further, that such a computer can be used programmatically to determine the output from a set of interacting molecular species in vitro. So programmed, the set performs automatically. It is an automaton.
Adar et al. (“Stochastic Computing with Biomolecular Automata” Proc. Nat'l Acad. Sci. 101:960-9965 (2004) reported on a similar computing automaton. The computer accepts “data” encoded in a DNA molecule and processes the data with one or more enzymes that digest DNA. The enzymes are analogous to computer hardware. Whether or not the “hardware” actually digests the input DNA, and in what way, depends on the specific composition of a mixture of molecules that affect the enzymes. Such mixtures, in effect, “program” the hardware. They are therefore analogous to the software that modern computers employ.
Whereas Benenson et al. relied on restriction enzymes (e.g., Fok1) to manipulate inputted DNA, Win et al., in “A Modular and Extensible RNA-Based Gene-Regulatory Platform for Engineering Cellular Function” PNAS 104(36):14283-14288 (2007), employed a hammerhead ribozyme (catalytic RNA) with “riboswitch” properties. The construct comprises (1) an aptamer specific for a pre-determined ligand (e.g., theophylline) and (2) a ribozyme coupled to the aptamer in such a way that when the aptamer binds (“senses”) the ligand, the ribozyme domain is actuated. Win et al. focused on attaining external control over gene expression. They did not suggest a means of introducing into a cell a system that would internally control gene expression.
Bayer et al., “Programmable Ligand-Controlled Riboregulators of Eukaryotic Gene Expression” Nat. Biotechnol. 23:337-343 (2005) described an RNA construct for controlling gene expression, the construct comprising an antisense domain and a ligand-sensitive aptamer domain. Aptamer-ligand binding changes the conformation of the construct. The resultant change may enable the antisense domain to interact with a target mRNA in a way that interferes with translation. The experiments described in the reference put the focus on introducing a switching mechanism into a cell in order to achieve external control over expression.
Another approach to suppressing gene expression is exemplified by Isaacs et al. in “Engineered Riboregulators Enable Post-Transcriptional Control of Gene Expression” Nat. Biotechnol. 22:841-847 (2004). Essentially, the technology sequesters the ribosome binding site on messenger RNA by “hiding” it in a fold or loop on messenger RNA. The technique requires engineering a mutation into the DNA that encodes the messenger RNA the engineer wishes to control. The mutation is a short sequence that transcribes into the 5′-untranslated region of the mRNA a nucleotide sequence complementary to the ribosome binding site. Hybridization then prevents the ribosome from recognizing the messenger.
Sumimoto et al., in Future Oncol., 3(6):655-64, (2007) and Sumimoto et al., in Int. J. Cancer, 118(2):472-6, (2006) have introduced siRNA, as such, into cells by means of lentiviral vectors, and Wiznerozicz et al., in J. Virol., 77(16):8957-8961, (2003) similarly introduced a construct that can be induced by drugs to express siRNA, but neither of these references suggests coupling siRNA expression to endogenous signals.
Not all living cells are under the control of a normally functioning control system. Cancer cells, for example, have a dysfunctional control system. Normal cells exchange and process numerous molecular signals in a generally coordinated fashion that is reflected in the ongoing integrity of the cell. Even when one or more of these signals is faulty, a normal cell readily detects the fault and initiates self-repair processes or, when necessary, apoptosis. Current cancer therapies such as surgery, chemotherapy and radiation treatment are highly aggressive methods of killing cells, notorious for causing collateral damage and equally notorious for missing their targets. What is needed are treatments directed at restoring enough self-control to cancerous cells, wherever they may be located in a patient's body, to allow them at least to eliminate themselves.